"Trying to Figure Out Where We Belong": Narratives of Racialized Sexual Minorities on Community, Identity, Discrimination, and Health
Bibliographic record
Abstract
Lesbian, Gay, Bisexual, Transgender, and Queer people of colour are regularly exposed to unique and contextual forms of prejudice and stigma, which have been linked to stress and increased likelihood of mental and physical health problems. In order to better understand the experiences of this multiply marginalized population, we interviewed eleven LGBTQ-POC to examine how they describe their identities, communities, health, and experiences with stigma. This study reveals new information about community intersection and the microaggressions experienced by queer people of colour, and provides theoretical support for previously identified issues concerning identity relationships and wellbeing. Common issues discussed by respondents include disconnect from communities, relationships between identities, coming out, exoticization, and stress and anxiety. Three primary concepts that are introduced and discussed in this study include:
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".